Teknoloji şirketleri yapay zeka modellerini açmaya yöneldi

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Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. Today, we cover one out of five topics from last week’s The Pulse issue. Full subscribers received the article below seven days ago. If you’ve been forwarded this email, you can subscribe here .

In May, I covered an emerging trend of companies wanting to cut back their AI spending, starting with engineering departments. Different approaches were being tried:

A few months later, it seems that several companies have managed to achieve this, according to sources I’ve spoken with.

Uber managed to blow through its annual AI budget in the first three months of this year, and it wasn’t a surprise to hear, in May, Uber’s COO say that it was getting harder to justify spending on tools like Claude Code without seeing benefits from the leading models.

It wasn’t long until engineering teams at the ridesharing giant set to work on how to optimize AI spend, and their efforts weren’t in vain.

Uber cut the cost per AI request by 34%, and the cost per AI session by 52%:

Of course, Uber keeps using more AI tokens and starting more AI sessions, but thanks to optimizations the cost has been flat since March, despite significantly more usage:

How did they pull it off at Uber? It was via a combination of different approaches:

From the outside, the single biggest win seems to be Uber’s transition to using open models for certain tasks. Open models cost 2-20x less, compared to frontier ones:

Interesting details from Pinterest’s earnings call last month reveal how much the social media platform saves by running open models. Here’s what CEO William Ready said (emphasis mine):

Basically, what used to cost Pinterest $100 to run on a closed, frontier model, they now spend $8 on by using open models on owned or rented inference!

With 100,000 employees, AT T is a big spender on AI.